Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
This article analyzes the impact of a computer simulation (business game) on the users' perceived learning. The theoretical model developed in this paper is derived from the ...
: This paper describes a new approach for the creation of an adaptive system able to selectively combine dynamic multidimensional information sources to perform state estimation. T...
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...